code: def train_dataloader(self):
      loaders = [
          DataLoader(
              torch.utils.data.ConcatDataset(self.train_datasets),
              batch_size=self.train_batch_sizes[0],
              num_workers=self.config.num_workers,
              pin_memory=True,
              worker_init_fn=self.seed_worker,
              generator=self.g,
              shuffle=True,
              collate_fn=self.ignore_none_collate,
          )
      ]
      return loaders
  
imports: import math
  import random
  from pathlib import Path
  import numpy
  import lightning.pytorch
  import torch
  from lightning.pytorch.utilities import rank_zero_only
  from torch.nn.utils.rnn import pad_sequence
  from torch.optim.lr_scheduler import LambdaLR
  from torch.utils.data import DataLoader
  from nougat import NougatConfig, NougatModel
  from nougat.metrics import get_metrics
label_desc: Use image node_id 2 for calling the NougatDataPLModule obj's underlying member method code with example usage: obj.train_dataloader() and returns: loaders